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Mechanistic models for predicting insect responses toclimate changeJames L Maino1, Jacinta D Kong1, Ary A Hoffmann1,Madeleine G Barton2 and Michael R Kearney1

Available online at www.sciencedirect.com

ScienceDirect

Mechanistic models of the impacts of climate change on

insects can be seen as very specific hypotheses about the

connections between microclimate, ecophysiology and vital

rates. These models must adequately capture stage-specific

responses, carry-over effects between successive stages, and

the evolutionary potential of the functional traits involved in

complex insect life-cycles. Here we highlight key

considerations for current approaches to mechanistic

modelling of insect responses to climate change. We illustrate

these considerations within a general mechanistic framework

incorporating the thermodynamic linkages between

microclimate and heat, water and nutrient exchange

throughout the life-cycle under different climate scenarios. We

emphasise how such a holistic perspective will provide

increasingly robust insights into how insects adapt and

respond to changing climates.

Addresses1 School of BioSciences, The University of Melbourne, Victoria 3010,

Australia2 Department of Conservation Ecology and Entomology, Centre for

Invasion Biology, Stellenbosch University, Private Bag X1, Stellenbosch,

Matieland 7602, South Africa

Corresponding author: Kearney, Michael R ([email protected])

Current Opinion in Insect Science 2016, 17:81–86

This review comes from a themed issue on Global change biology/

molecular physiology

Edited by Vladimir Kostal and Brent J Sinclair

http://dx.doi.org/10.1016/j.cois.2016.07.006

2214-5745/# 2016 Published by Elsevier Inc.

Correlation versus mechanism in modellinginsect responses to climate changeBiology has entered the age of data. Our access to informa-

tion, and its rate of accumulation, is unprecedented. The

sheer resolution of data available for use has led to new

statistical methods and computational techniques that are

able to describe and predict complex relationships between

variables [1,2]. Correlative approaches for analysing detailed

data are important tools in a variety of applications. However,

when projecting to novel scenarios, correlative models make

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one crucial assumption: that the relationships inferred from

observed data will hold beyond the range of our observa-

tions. This issue is of particular concern when trying to

predict species’ responses to climate change, which will

present novel environments to organisms [3,4��,5].

To make predictions of insect responses to climate

change we require models that behave realistically under

novel scenarios [4��]. Mechanistic models can be defined

as those that explicitly incorporate a system’s sub-pro-

cesses to predict a response, as opposed to a model

concerned with the statistical description of a phenome-

non [6]. For this reason, mechanistic models are less

vulnerable to the well-known pitfalls of extrapolation

(Figure 1). The main trade-off is that we require an in-

depth knowledge of the components relevant to predict-

ing a particular system, such as classical mechanics in

Figure 1. Predicting insect responses to climate change

requires an understanding of how their underlying phys-

iology, homeostatic requirements, and adaptive potential

mediate their responses to changing environments.

Various processes occurring at molecular or ecological

levels are involved in how organisms respond to climate,

but each can be expressed in the universal currencies of

energy and mass, which must be conserved irrespective of

the scale of inquiry. Insect behaviour is largely driven by a

need to meet certain homeostatic requirements. Stoichio-

metric homeostasis causes insects to preferentially select

food that contains more of a required nutrient [7,8].

Likewise, ectothermic insects must defend their thermal

target by behaviourally regulating body-temperature

through the selection of different microhabitats [9–11].

Nutritional and thermal demands also interact strongly

with water requirements [12]. The ability to meet these

requirements determines rates of development, growth

and reproduction, which obey universal energetic con-

straints across a wide range of insects and life-stages

[13,14,15�,16�]. Such potential rates interact with the

seasonal windows for development, growth and reproduc-

tion, necessitating appropriate phenological responses

[17,18]. In turn, generation times and reproductive output

affect rates of evolution and an insect’s ability to adapt to

new selection pressures [19]. Although insects have sig-

nificant adaptive ability compared to other animals, they

must nonetheless obey these fundamental constraints.

Here we outline some important considerations when

developing mechanistic models aiming to predict insect


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82 Global change biology/molecular physiology

Figure 1

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Current Opinion in Insect Science

Mechanistic models can be particularly useful for prediction under

novel circumstances. Using the observed trajectory of a grasshopper

in flight, extrapolation by a correlative model makes an unrealistic

prediction of the grasshopper’s future position. Building the laws of

motion into a mechanistic model, such as gravity and air resistance,

improves the prediction and applies anywhere these physical rules

operate, for example, on a novel planet. Likewise, building in known

biological processes into mechanistic models will improve predictions

of species’ responses to novel climatic circumstances.

responses to environmental change. Key issues include

stage-specific considerations of insect life-cycles, the

microclimates they inhabit, and their adaptive potential.

Most of these issues were emphasised 85 years ago by

Uvarov in his manifesto on insects and climate [20], which

distilled 1100 papers on the responses of insects to

climate. Here we aim to show how, with the application

of new thermodynamically-based modelling approaches,

Uvarov’s vision can now be more readily achieved.

Microclimates: the environmental stage forthe insect energy budgetThe ecological diversity of insects is reflected in the range

of microclimates they inhabit which in turn influence

insect physiology [21]. These microclimates vary greatly

and may act as buffers or amplifiers of weather conditions

[22,23��,24]. Within soil, microclimate conditions vary

with depth and soil type, whereby soil microclimates

can buffer above-ground conditions even at near-surface

soil layers [21,25]. The interactions between insects and

biotic habitats such as plants generates highly variable

microclimates, which are often dominated by host plant

physiology rather than weather conditions [26].

Microclimatic conditions can be measured directly but

manually collecting such data at ecologically relevant

temporal and spatial scales is usually unfeasible

[5,27��]. Alternatively, we can exploit the physics of


energy and mass exchange, as well as historical and

projected climatic data, to estimate microclimates across

large scales of time and space [28]. Behavioural strategies

regulate the selection of microclimates and determine

heat and water budgets [23��]. With enough information,

a model that combines microclimatic options and beha-

vioural strategies can be constructed to infer an orga-

nism’s heat and water budget and, thus, vital rates

through time (Figure 2) [29�].

Matching the microclimate to the life-cyclestageLife-stages of insects differ in mobility, and thus expo-

sure to microclimate variability. The survival of immobile

life-stages, such as eggs or pupae, is closely tied to their

microenvironment, which may be behaviourally selected

by preceding life-stages [30]. The microclimatic variation

between successive stages in a life-cycle must be ade-

quately captured in mechanistic models, including stage-

specific sensitivities and fitness measures [31–33,34�].Additionally, as the body size of adult insects is usually

fixed by pupation, nutrients acquired during the larval

stage strongly determines reproductive output, and adult

fitness in general [35,36].

A range of physiologically-based models have been de-

veloped that use statistical descriptions of observed

growth and development to predict stage specific

responses [37–43]. Detailed species-specific models de-

rived from statistical descriptions of experimental data or

of particular microclimates can be highly successful [44].

More generality and robustness to novel conditions can

potentially be achieved if models are developed from

general theories about metabolism which are grounded in

thermodynamic principles. A promising approach is to

develop models based on Dynamic Energy Budget

(DEB) theory that integrate the dynamic processes of

growth, development, maintenance and reproduction

throughout the life-cycle as a function of temperature

and food availability [45]. At each stage the organism’s

energy and mass budget depends on the conditions

experienced in previous stages. Such models have been

used to explain species-specific phenomena [16�] and also

general energetic patterns within stages that hold across

species [14,46]. A key advantage of the DEB framework is

its generic nature, leading to its application to hundreds of

diverse species from bacteria to vertebrates [47].

Evolutionary responses to changing climatesAlthough insects possess varied behavioural and physio-

logical mechanisms to help them mitigate the effects of

changing environments [48�], the capacity for adaptation

via evolution will further determine a species’ success.

Attempts to understand the evolutionary responses of

insects to changing environmental conditions, including

climate change, have focussed on various life-history

responses or traits such as thermal resistance [49,50].


Mechanistic models of climate change responses Maino et al. 83

Figure 2

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Current Opinion in Insect Science

Model predictions for Heteronympha merope include growth trajectories and microclimate estimates under four simulation scenarios (top-left:

baseline; top-right: warming; bottom-left: larger body-size; bottom-right: warming and larger body-size). The simulations were implemented in the

R package NicheMapR. Body temperatures of the different life-history stages within their respective microclimates were determined at each hour

of the simulation, and temperature-dependent physiological rates, including growth and maturation (development), were estimated from published

datasets (Barton et al. in prep). Development and growth through the annual life-cycle of H. merope is tracked throughout the simulation, shown in

the corresponding growth trajectory figures, in which the solid blue line represents the food water content as driven by soil moisture (dips in the

line represent dry spells). The active stages (larvae and imago) were allowed to thermoregulate behaviourally within their microclimates. Hours in

which predicted body temperature could facilitate sustained activity are indicated by the grey line in the microclimate figure. The points where the

chosen depth drops 15 cm (brown line) indicate retreat to deep, humid conditions until the next rainfall event. Shade selection (dark green line) in

the nocturnal larval stages acts to make the animal warmer and is thus reduced under warming, in contrast to the diurnal adult stage. Predicted

body temperatures in these different states (red line), as well as the corresponding air temperature (at 1.2 m high, light blue line) for each, hour are

also shown.

Typically, such traits are assessed for variation across and

within populations, using quantitative genetic approaches

to assess the heritability of traits and how far they can be

shifted under directional selection. Between-population

studies tend to focus on the extent to which population

variation is genetically determined, through transplant

experiments or, more commonly, comparisons in common

environments.


Mechanistic models can be used to identify the types of

traits and environmental conditions that should be

assessed in determining whether insects are able to adapt

through evolution under climate change [51]. Models can

then explore the role of heritable variation and likelihood

of evolutionary shifts in survival and distribution under

climate change [52,53�]. Such models are expected to

improve predictions, and lead to an understanding of



adaptive changes that are predicted to occur or that have

already been observed.

Mechanistic models combining genetic variation and

predicted impacts of climate change can also be used to

explore cases where evolved responses might be

expected, but have not yet occurred. Such evolutionary

delays to adaptation may occur in plant-insect systems

that are dependent on phenological synchrony between

insects and their host plant, where each trophic level has

specific sensitivities and evolvability under climate

change [54,55]. These sensitivities can be better quan-

tified by recent advances in the molecular basis of

temperature responses, which feed into mechanistic

models that predict seemingly complex phenological

responses with the regulatory dynamics of only a small

number of genes [56].

Mechanistic models may also be useful in identifying

the types of traits likely to exhibit evolutionary con-

straints and reduced adaptive potential under climate

change. Insect traits are expected to show reduced

narrow-sense heritability and evolvability as they ap-

proach extremes within this space, unless there are

some major adjustments in an organism’s development.

Low evolvabilities occur commonly for traits scored in

insects [57] but they are rarely considered from the

perspective of potential limits [58]. Conversely, by

identifying limits to evolutionary changes in develop-

ment, voltinism and thermal performance, evolutionary

studies can help define the parameter space within

which traits can be altered, or where traits are invariable

and result in vulnerability [59]. Trait limits associated

with climate change vulnerability should be testable

through a phylogenetic framework [60]. Such analyses

have highlighted lineages where evolutionary shifts are

expected to be achievable as opposed to being con-

strained due to phylogenetic inertia [58].

Mechanistically modelling insect responses tochanging climate: an exampleTo predict how insect phenologies and life-cycle bioen-

ergetics will respond to changing climates, mechanistic

models must ideally account for the microclimatic, stage-

specific, and evolutionary processes discussed above. To

illustrate how this can be achieved, we provide an exam-

ple analysis of from a model we are developing for the

Common Brown butterfly, Heteronympha merope(Figure 2). This species has an annual life-cycle, and

we aim to predict how changes in climate might alter the

timing of adult emergence, and whether evolution to a

larger adult body size leads to further shifts in phenology.

To begin, the microclimates of each life-history stage are

estimated using the NicheMapR package (https://github.

com/mrke/NicheMapR/releases). Although the larval and

imago stages can behaviourally buffer themselves against


unfavourable environments by seeking shade and moving

underground to more suitable hydric and thermal condi-

tions, the egg and pupal stages remain at a fixed location.

With our estimates of microclimate conditions, the life-

cycle energetics (developmental, growth, condition, and

reproduction) of the Common Brown are then captured

by an insect DEB model (detailed in [16�]). The effect of

evolution to a larger body size (and associated life-history

trade-offs [61]) is compared assuming heritable genetic

variation for size available to selection. Finally, climatic

conditions under a moderate warming scenario are tested

by adding 3 8C to the air temperature data from which

microclimates are derived.

We see a strong effect of warming on earlier larval stages

because these stages have a greater sensitivity to tem-

perature, despite their capacity to behaviourally ther-

moregulate (Figure 2) [62]. Large shifts in phenology

are observed, with pupation occurring earlier in the year

under warming [63]. The adult consequently emerges

earlier in spring in the warming scenario, potentially

reducing survival to the next suitable oviposition time

in autumn because of life-span constraints. The effect

of warming on soil moisture early in the year is also

particularly pronounced. However, there is no major

predicted phenological effect of a 1.7-fold increase in

body size.

Concluding remarksIn 1931, Uvarov wrote that predicting insect responses

into the future ‘can be done only on the basis of a most

intimate knowledge of the pest and of its relations to its

environment, i.e., of a thorough understanding of the

whole bewildering complex of environmental factors

and of the responses thereto of the insect’. Mechanistic

models based on fundamental and general physical prin-

ciples go some way to incorporating this complexity, and

can be particularly powerful at capturing the direct

impacts of climate.

One impediment to mechanistic modelling is the large

biological data requirement for model parameterisation.

This burden will lessen as methods emerge for more

efficiently phenotyping individuals, which will lower

the costs of obtaining required inputs for the model.

For example, the thermal response of insect eggs to

temperature gradients and diurnal cycles can be explored

experimentally through rearing them in thermocyclers

[64��]. Insects in particular will benefit from such tech-

nologies due to their small size and fast development

times.

Biotic interactions and evolutionary responses loom as an

additional challenge in the complex puzzle of insect

responses to climate change. But, as Uvarov also said,

‘It is possible to imagine an insect with no natural ene-

mies and without any need to compete for food, shelter,


https://github.com/mrke/NicheMapR/releases

https://github.com/mrke/NicheMapR/releases

Mechanistic models of climate change responses Maino et al. 85

etc., . . . but an insect living under natural conditions and

yet free from climatic influences is an absurdity’ [20].

Capturing the direct climatic responses with the kind of

detail we illustrate in our example above permits us to at

least define the boundaries of the problem — that is, to

lay out the ‘thermodynamic edge pieces’ of the puzzle

[65]. We are then in a stronger position to tackle other

kinds of interactions that may be needed for sufficient

realism. For these reasons we expect mechanistic models,

and the underpinning science on which they are built, to

become increasingly important tools for predicting and

understanding insect responses to climate change.

AcknowledgementsWe thank E. Pirtle for her illustration in Figure 1. Work on the CommonBrown Butterfly was supported by the Australian Research Council(DP0772837).

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64.��

Kong J, Axford J, Hoffmann A, Kearney MR: Novel applications ofthermocyclers for phenotyping invertebrate thermalresponses. Methods Ecol Evol (Online Early View) 2016. [novolume].

An example of how modern techniques can reduce the cost associatedwith obtaining data inputs required for the parameterisation of mechan-istic models.

65. Kearney MR: Activity restriction and the mechanistic basisfor extinctions under climate warming. Ecol Lett 2013,16:1470-1479.































































































































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